Displacement measurements in semiconductor wafer processing

ABSTRACT

Wafers that begin as flat surfaces during a semiconductor manufacturing process may become warped or bowed as layers and features are added to an underlying substrate. This warpage may be detected between manufacturing processes by rotating the wafer adjacent to a displacement sensor. The displacement sensor may generate displacement data relative to a baseline measurement to identify areas of the wafer that bow up or down. The displacement data may then be mapped to locations on the wafer relative to an alignment feature. This mapping may then be used to adjust parameters in subsequent semiconductor processes, including adjusting how a carrier head on a polishing process holds or applies pressure to the wafer as it is polished. A model may be trained to provide control signals for a polishing/cleaning process, or to generate metrology data.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. application Ser. No. 17/334,407 filed on May 28, 2021, which is incorporated herein by reference.

TECHNICAL FIELD

This disclosure generally relates to measuring warpage of a wafer between semiconductor manufacturing processes. Specifically, this disclosure describes measuring displacement data around a wafer to characterize a warp/bow in the wafer, then using the displacement data to control subsequent processes to compensate for the warp/bow.

BACKGROUND

An integrated circuit is typically formed on a substrate by the sequential deposition of conductive, semiconductive, and/or insulative layers on a silicon wafer. A variety of fabrication processes use the planarization of a layer on the substrate between processing steps. For example, for certain applications, e.g., polishing of a metal layer to form vias, plugs, and/or lines in the trenches of a patterned layer, an overlying layer is planarized until the top surface of a patterned layer is exposed. In other applications, e.g., planarization of a dielectric layer for photolithography, an overlying layer is polished until a desired thickness remains over the underlying layer.

Chemical mechanical polishing (CMP) is one common method of planarization. This planarization method typically requires that the substrate be mounted on a carrier or polishing head. The exposed surface of the substrate is typically placed against a rotating polishing pad. The carrier head provides a controllable load on the substrate to push it against the polishing pad. Abrasive polishing slurry is typically supplied to the surface of the polishing pad.

One problem in CMP and other semiconductor processes is maintaining a consistent surface on the wafer. Even though the wafer may begin as a silicon crystal that is relatively flat, various semiconductor processes may deposit, grow, add, etch, remove, and/or otherwise place layers or features on the wafer. These additional layers and features may build up and cause stresses to occur in the wafer. The stresses may then cause the wafer to bow or warp. This warpage may cause problems when polishing or cleaning the surface of the wafer the surface of the wafer may no longer be uniform.

SUMMARY

In some embodiments, a system may include a platform configured to support a wafer and rotate a wafer around a center of the wafer; and one or more displacement sensors positioned to measure a displacement of the wafer as the wafer is rotated.

In some embodiments, a method of measuring displacement of wafers between semiconductor manufacturing processes may include rotating a wafer around a center of the wafer; measuring a displacement of the wafer at a predetermined distance from the center of the wafer as the wafer is rotated to generate displacement data; and using the displacement data to control a polishing process or a cleaning process performed on the wafer.

In some embodiments, a non-transitory computer-readable medium may include instructions that, when executed by one or more processors, cause the one or more processors to perform operations including receiving, for a wafer, displacement data generated using a displacement sensor, where the displacement data may indicate an area on the wafer that is bowed or warped; identifying a parameter of a carrier head corresponding to a location of the area on the wafer that is bowed or warped, where the carrier head may be part of a chemical-mechanical polishing (CMP) machine or a wafer cleaning machine; and adjusting the parameter of the carrier head to compensate for the area on the wafer that is bowed or warped during a cleaning or polishing process.

In any embodiments, any and all of the following features may be implemented in any combination and without limitation. The system may also include an alignment sensor positioned to detect a notch in the wafer as the wafer is rotated. The one or more displacement sensors may include a laser displacement sensor; and the alignment sensor may include a through-beam sensor. The one or more displacement sensors may also be positioned to detect a notch in the wafer as the wafer is rotated. The one or more displacement sensors may include a displacement sensor positioned above the wafer. The one or more displacement sensors may include a displacement sensor positioned below the wafer. The one or more displacement sensors may include a plurality of displacement sensors positioned along a radial line of the wafer. The one or more displacement sensors may include a plurality of displacement sensors positioned at different rotational angles around the wafer. The method/operations may also include measuring a displacement of a baseline wafer to generate baseline displacement data representing a flat wafer surface. Generating the displacement data may include determining a displacement of the wafer relative to the baseline displacement data. The method/operations may also include mapping the displacement data to two-dimensional coordinates on the wafer based on alignment data. The method/operations may also include mapping the displacement data to angles of rotation on the wafer based on alignment data. The method/operations may also include identifying a displacement area on the wafer in the displacement data, and providing the displacement area to the polishing process or the cleaning process. Adjusting the parameter of the carrier head may include adjusting an angle at which the carrier head grips the wafer during the cleaning or polishing process. Adjusting the parameter of the carrier head may include adjusting an amount of pressure provided against the area on the wafer that is bowed or warped during the cleaning or polishing process. Adjusting the amount of pressure may include identifying a chamber in the carrier head that is adjacent to the area on the wafer that is bowed or warped; and adjusting a pressure in the chamber to compensate for the area on the wafer that is bowed or warped. Adjusting the amount of pressure may include adjusting a pressure with which a brush cleans the area on the wafer that is bowed or warped during the cleaning process. The displacement data may be generated using the displacement sensor by rotating the displacement sensor around the wafer.

In some embodiments, a system may include one or more displacement sensors positioned to measure a displacement of a wafer as the wafer is rotated on a platform; a cleaning or polishing chamber configured to clean or polishing the wafer; and a computer system configured to perform operations that may include receiving, for the wafer, displacement data generated using the one or more displacement sensors, where the displacement data may indicate displacement of the wafer relative to the one or more displacement sensors; providing the displacement data to a model that is trained using displacement data sets; generating control signals for the cleaning or polishing chamber based on output from the model in response to receiving the displacement data as input; and using the control signals to control the cleaning or polishing process for the wafer.

In some embodiments, a method may include receiving, for a wafer, displacement data generated using a displacement sensor, where the displacement data may indicate displacement of the wafer relative to the displacement sensor; providing the displacement data to a model that is trained using metrology data sets and corresponding displacement data sets; and generating metrology data for the wafer based on output from the model in response to receiving the displacement data as input to the model.

In some embodiments, a non-transitory computer-readable medium may include instructions that, when executed by one or more processors, cause the one or more processors to perform operations including receiving, for a wafer, displacement data generated using a one or more displacement sensors, where the displacement data may indicate displacement of the wafer relative to the one or more displacement sensors; providing the displacement data to a model that is trained using displacement data sets; and generating control signals for a cleaning or polishing chamber based on output from the model in response to receiving the displacement data as input.

In any embodiments, any and all of the following features may be implemented in any combination and without limitation. Controlling the cleaning or polishing process for the wafer may include selecting the cleaning or polishing process from a plurality of different cleaning or polishing processes, where the cleaning or polishing process may have a shorter run time than at least one of the plurality of different cleaning or polishing processes. Controlling the cleaning or polishing process for the wafer may include controlling a rotation speed of a platen that supports the wafer in the cleaning or polishing process. Controlling the cleaning or polishing process for the wafer may include controlling a rotation speed of a cleaning or polishing head in the cleaning or polishing process. Controlling the cleaning or polishing process for the wafer may include controlling a flow of slurry used in the cleaning or polishing process. Controlling the cleaning or polishing process for the wafer may include controlling a pressure applied to a zone in a cleaning or polishing head in the cleaning or polishing process. The displacement data may indicate an area on the wafer that is bowed or warped. The method/operations may also include using the metrology data to control a cleaning or polishing process for the wafer. The metrology data may include thicknesses of thin films or features on the wafer. The method/operations may also include rotating a wafer around a center of the wafer, measuring a displacement of the wafer at a predetermined distance from the center of the wafer as the wafer is rotated to generate the displacement data, and/or measuring a displacement of a baseline wafer to generate baseline displacement data representing a flat wafer surface. Generating the displacement data may include determining a displacement of the wafer relative to the baseline displacement data. The method/operations may also include mapping the displacement data to two-dimensional coordinates on the wafer based on alignment data or mapping the displacement data to angles of rotation on the wafer based on alignment data. The method/operations may also include identifying a displacement area on the wafer in the displacement data, and providing the displacement area to the polishing or cleaning process.

BRIEF DESCRIPTION OF THE DRAWINGS

A further understanding of the nature and advantages of various embodiments may be realized by reference to the remaining portions of the specification and the drawings, wherein like reference numerals are used throughout the several drawings to refer to similar components. In some instances, a sub-label is associated with a reference numeral to denote one of multiple similar components. When reference is made to a reference numeral without specification to an existing sub-label, it is intended to refer to all such multiple similar components.

FIG. 1 illustrates a schematic cross-sectional view of an example of a polishing apparatus, according to some embodiments.

FIG. 2 illustrates a measured spectrum from the in-situ optical monitoring system, according to some embodiments.

FIG. 3 illustrates a path of a sequence of spectral measurements on the substrate, according to some embodiments.

FIG. 4 illustrates a system for measuring wafer displacement, according to some embodiments.

FIG. 5A illustrates a displacement sensor positioned at the edge of the wafer, according to some embodiments.

FIG. 5B illustrates a displacement sensor positioned to measure a displacement of the bottom edge of the wafer, according to some embodiments.

FIG. 5C illustrates a plurality of displacement sensors, according to some embodiments.

FIG. 5D illustrates a plurality of displacement sensors positioned at different rotational angles, according to some embodiments.

FIG. 6 illustrates a three-dimensional graph of displacement data, according to some embodiments.

FIG. 7A illustrates a baseline wafer that may be measured by a displacement sensor, according to some embodiments.

FIG. 7B illustrates a convex wafer, according to some embodiments.

FIG. 7C illustrates a concave wafer, according to some embodiments.

FIG. 8 illustrates a graph of displacement data for warped wafers, according to some embodiments.

FIG. 9 illustrates a flowchart of different processes the may be executed as part of a semiconductor manufacturing process, according to some embodiments.

FIG. 10 illustrates a flowchart of a method for measuring displacement of wafers during semiconductor manufacturing processes, according to some embodiments.

FIG. 11 illustrates a block diagram of a process for training a model, according to some embodiments.

FIG. 12 illustrates a block diagram of a system for using a trained model to control a cleaning or polishing process, according to some embodiments.

FIG. 13 illustrates a block diagram of a process for using a model to generate control signals for a cleaner polishing process, according to some embodiments.

FIG. 14 illustrates a block diagram of how the model may be used to produce metrology data, according to some embodiments.

FIG. 15 illustrates a flowchart of a method for training and using a model with displacement data, according to some embodiments.

FIG. 16 illustrates an exemplary computer system, in which various embodiments may be implemented.

DETAILED DESCRIPTION

FIG. 1 illustrates an example of a polishing apparatus 100. The polishing apparatus 100 may include a rotatable disk-shaped platen 120 on which a polishing pad 110 may be situated. The platen may be operable to rotate about an axis 125. For example, a motor 121 may turn a drive shaft 124 to rotate the platen 120. The polishing pad 110 may be a two-layer polishing pad with an outer polishing layer 112 and a softer backing layer 114.

The polishing apparatus 100 may include a port 130 to dispense polishing liquid 132, such as slurry, onto the polishing pad 110. The polishing apparatus may also include a polishing pad conditioner to abrade the polishing pad 110 to maintain the polishing pad 110 in a consistent abrasive state.

The polishing apparatus 100 may include at least one carrier head 140. The carrier head 140 may be operable to hold a substrate 10 against the polishing pad 110. The carrier head 140 may have independent control of the polishing parameters, for example pressure, associated with each respective substrate.

In particular, the carrier head 140 may include a retaining ring 142 to retain the substrate 10 below a flexible membrane 144. The carrier head 140 may also include a plurality of independently controllable pressurizable chambers defined by the membrane, e.g., three chambers 146 a-146 c, which may apply independently controllable pressures to associated zones on the flexible membrane 144 and thus on the substrate 10. Although only three chambers are illustrated in FIG. 1 for ease of illustration, there could be one or two chambers, or four or more chambers, e.g., five chambers in other embodiments.

The carrier head 140 may be suspended from a support structure 150, e.g., a carousel or a track, and may be connected by a drive shaft 152 to a carrier head rotation motor 154 so that the carrier head can rotate about an axis 155. Optionally the carrier head 140 may oscillate laterally, e.g., on sliders on the carousel 150 or track; or by rotational oscillation of the carousel itself. In operation, the platen may be rotated about its central axis 125, and the carrier head may be rotated about its central axis 155 and/or translated laterally across the top surface of the polishing pad.

While only one carrier head 140 is shown, more carrier heads may be provided to hold additional substrates so that the surface area of polishing pad 110 may be used efficiently.

The polishing apparatus may also include an in-situ monitoring system 160. The in-situ monitoring system may generate a time-varying sequence of values that depend on the thickness of a layer on the substrate. The in-situ-monitoring system 160 may include an optical monitoring system. In particular, the in-situ-monitoring system 160 may measure a sequence of spectra of light reflected from a substrate during polishing.

An optical access 108 through the polishing pad may be provided by including an aperture (i.e., a hole that runs through the pad) or a solid window 118. The solid window 118 may be secured to the polishing pad 110, e.g., as a plug that fills an aperture in the polishing pad. The solid window may alternatively be molded to or adhesively secured to the polishing pad, although in some implementations the solid window can be supported on the platen 120 and project into an aperture in the polishing pad.

The optical monitoring system 160 may include a light source 162, a light detector 164, and circuitry 166 for sending and receiving signals between a remote controller 190, e.g., a computer, and the light source 162 and light detector 164. One or more optical fibers can be used to transmit the light from the light source 162 to the optical access in the polishing pad, and to transmit light reflected from the substrate 10 to the detector 164. For example, a bifurcated optical fiber 170 may be used to transmit the light from the light source 162 to the substrate 10 and back to the detector 164. The bifurcated optical fiber may include a trunk 172 positioned in proximity to the optical access, and two branches 174 and 176 connected to the light source 162 and detector 164, respectively.

In some implementations, the top surface of the platen can include a recess 128 into which is fit an optical head 168 that holds one end of the trunk 172 of the bifurcated fiber. The optical head 168 may include a mechanism to adjust the vertical distance between the top of the trunk 172 and the solid window 118.

The output of the circuitry 166 may be a digital electronic signal that passes through a rotary coupler 129, e.g., a slip ring, in the drive shaft 124 to the controller 190 for the optical monitoring system. Similarly, the light source may be turned on or off in response to control commands in digital electronic signals that pass from the controller 190 through the rotary coupler 129 to the optical monitoring system 160. Alternatively, the circuitry 166 may communicate with the controller 190 by a wireless signal.

The light source 162 may be operable to emit ultraviolet (UV), visible light, or near-infrared (NIR) light. The light detector 164 may be a spectrometer. A spectrometer is an optical instrument for measuring intensity of light over a portion of the electromagnetic spectrum. For example, a grating spectrometer may be used. Typical outputs for a spectrometer may include the intensity of the light as a function of wavelength (or frequency). FIG. 2 illustrates an example of a measured spectrum 200 with intensity as a function of wavelength.

As noted above, the light source 162 and light detector 164 may be connected to a computing device, e.g., the controller 190, operable to control their operation and receive their signals. The computing device may include a microprocessor situated near the polishing apparatus. For example, the computing device may be a programmable computer. With respect to control, the computing device may, for example, synchronize activation of the light source with the rotation of the platen 120. A display 192, e.g., an LED screen, and a user input device 194, e.g., a keyboard and/or a mouse, may be connected to the controller 190.

In operation, the controller 190 may receive, for example, a signal that carries information describing a spectrum of the light received by the light detector for a particular flash of the light source or time frame of the detector. Thus, this spectrum may be a spectrum measured in-situ during polishing. Without being limited to any particular theory, the spectrum of light reflected from the substrate 10 may evolve as polishing progresses due to changes in the thickness of the outermost layer, thus yielding a sequence of time-varying spectra.

The optical monitoring system 160 may be configured to generate a sequence of measured spectra at a measurement frequency, or “spectral data.” The relative motion between the substrate 10 and the optical access 108 causes spectra in the sequence to be measured at different positions on the substrate 10. In some implementations, the light beam generated by the light source 162 may emerge from a point that rotates (shown by arrow R in FIG. 3 ) with the platen 120. As shown in FIG. 3 , in such an implementation, the relative motion between the substrate 10 and the optical access 108 can cause spectra to be measured at positions 300 in a path across the substrate 10. In some implementations only one spectrum is measured per rotation of the platen. In addition, in some implementations, the emitting point of the light beam is stationary and measurements are taken only when the optical access 108 aligns with the light beam.

A CMP process represents one of many different processes that may be carried out during the manufacture of a semiconductor wafer. As different layers and features are added to the substrate, the CMP process may be used to planarize the wafer and remove specific amounts of material between stages. Ideally, the wafer may begin as a silicon crystal substrate that is completely flat. However, as layers and features are added to the substrate, this additional material adds stress to the structure and may cause warpage or bowing in the wafer. This warpage may cause problems during the CMP process, as the wafer may be polished unevenly, resulting in layers that do not have a uniform thickness after the CMP process is complete.

The embodiments described herein solve these and other technical problems by characterizing a vertical displacement of the wafer between semiconductor manufacturing processes. A displacement measurement may be made around a circumference of the wafer using a displacement sensor. The resulting displacement data may then be used to control a polishing process, a cleaning process, and/or an angle or orientation at which the wafer is handled. This allows a subsequent semiconductor process to compensate for the warpage of the wafer.

FIG. 4 illustrates a system 400 for measuring wafer displacement, according to some embodiments. The system 400 may include a platform 412 configured to support a wafer 404 and rotate the wafer 404 around a central axis 414 of the wafer 404. For example, before being placed in a CMP machine, an operator or a robotic arm may place the wafer 404 on the platform 412. The platform 412 may then rotate the wafer 404 around the central axis 414. Various sensors may measure attributes of the wafer 404 during rotation.

In some embodiments, the system 400 may include an alignment sensor. The alignment sensor may be implemented using a through-beam sensor that is configured to pass a beam of light between a first component 401 and a second component 403. The alignment sensor may be configured to detect when the beam is interrupted between the first component 401 and the second component 403. The alignment sensor may thus be used in conjunction with the rotation of the wafer 404 provided by the platform 412 to align the wafer 404 to a predefined orientation. For example, the wafer 404 may include a notch 416 or other edge feature along an outer circumference of the wafer 404. Normally, the wafer 404 will block the beam between the first component 401 and the second component 403 as the wafer 404 rotates around the central axis 414. However, when the notch 416 location along the edge of the wafer 404 passes above the first component 401 of the alignment sensor, the beam may be detected by the second component 403, thus indicating the location of the notch 416.

Once the location of the notch 416 is identified in the wafer 404, the system 400 may optionally rotate the wafer 404 to a predetermined orientation. For example, in some cases the system 400 may stop rotation of the wafer 404 when the notch 416 is located. In other cases, the system 400 may continue rotating the wafer 404 until a predetermined angle of rotation is reached. This process performed by the system 400 may be used to ensure that the wafer 404 is rotated to a known orientation before being moved into a subsequent machine in the semiconductor manufacturing process. For example, some systems may use robotic arms to handle the wafer 404 as it moves between various machines. Before being placed on the polishing pad of the CMP machine (or any other semiconductor manufacturing machine), the wafer 404 may be rotated into a known position. As described below, this alignment and rotational orientation of the wafer 404 may also be used to identify locations on the wafer 404 that are bowed or warped.

The system 400 may be implemented at least in part by a machine referred to as an aligner. Specifically, an aligner may be configured to rotate the wafer 404 until the notch 416 is located. In some embodiments, the aligner may be modified to also perform distance or displacement measurements on the wafer 404 as it rotates. The system 400 may further include a displacement sensor 406. As used herein, the term “displacement sensor” may include any sensor configured to measure a distance of a surface from the sensor. Some embodiments may use a laser displacement sensor as an example. A laser displacement sensor may emit one or more laser beams directed at the surface of the wafer 404 and receive reflections from the wafer 404. The displacement sensor 406 may then calculate a distance between the displacement sensor 406 and a surface of the wafer 404 on which the laser beam is directed. As the wafer 404 is rotated around the center axis 414, the displacement sensor 406 may continuously sample a distance measurement relative to the surface of the wafer 404.

When modifying an aligner, the system 400 may also include a computer system that controls and/or records displacement data received from the displacement sensor 406. The computer system may include one or more processors (e.g., microprocessors, microcontrollers, digital controllers, FPGAs, programmable hardware, and/or the like) that are configured to control the operation of the displacement sensor 406 and record displacement data. The one or more processors may be an integrated part of the system 400. Alternatively, the one or more processors may be part of a separate computer system that communicates with the displacement sensor 406 through a wired or wireless interface. Instructions for controlling the displacement sensor 406 may be stored on one or more memory devices, such as a non-transitory computer-readable medium, and these instructions may cause the one or more processors to perform operations such as receiving and processing displacement data, rotating the wafer 404, repackaging the displacement data, and so forth. An example of a computer system is described below in FIG. 11 .

The displacement sensor may be positioned to measure a displacement of the wafer 404 as the wafer 404 is rotated. Measuring the displacement of the wafer 404 may generate displacement data. The displacement data may include a distance measurement from the displacement sensor 406 to the wafer 404. Alternatively, the displacement data may include a displacement of the wafer 404 from a baseline location. For example, a baseline location for the wafer 404 may be determined by measuring displacement data for a bare silicon substrate or other wafer that is known to be flat as a reference. If the wafer 404 bows downward such that the displacement measurement is longer than the baseline displacement, the displacement data may include negative values. If the wafer 404 bows upward such that the displacement measure is shorter than the baseline displacement, the displacement data may include corresponding positive values.

The example of FIG. 4 includes a system 400 that combines an aligner and a displacement sensor 406. However, instead of modifying the aligner to include the displacement sensor 406, other systems may omit the aligner and provide a dedicated displacement sensor with a platform that rotates the wafer 400. In other embodiments, the displacement sensor 406 may itself rotate around the central axis 414 while the wafer 404 remains stationary. In these embodiments, the displacement sensor itself may take the place of the aligner and perform the alignment function with the displacement sensor 406. For example, the displacement sensor 406 may collect the displacement data and detect the location of the notch 416.

FIG. 5A illustrates a displacement sensor 506 a positioned at the edge of the wafer 504, according to some embodiments. In the example of FIG. 4 above, the displacement sensor 506 may be aimed at an outer edge of the wafer. For example, the outer edge of the wafer may include the outermost 1 cm of the wafer 504 such that the displacement measurement characterizes the displacement along the outer edge of the wafer 504. This position of the displacement sensor 506 a may provide specific technical advantages. Specifically, a bow or warping of the wafer 504 may be most pronounced at the edge. Since the wafer 504 is mounted at a center portion of the wafer 504 on the platform, the greatest displacement may be measured along the edge of the wafer 504. Additionally, when aimed at the edge of the wafer, the displacement sensor 506 a may also perform the function of the aligner. Specifically, the displacement sensor 506 a may continuously sample displacement measurements from the wafer 504. When the notch is encountered in the wafer 504, the displacement measurement may exceed a negative threshold distance, and the displacement sensor 506 a may interpret this measurement as the location of the notch. Thus, the displacement sensor 506 a may determine the orientation and the displacement data for the wafer 504.

FIG. 5B illustrates a displacement sensor 506 b positioned to measure a displacement of the bottom edge of the wafer 504, according to some embodiments. Instead of being positioned above the wafer 504 as illustrated in FIG. 5A, the displacement sensor 506 b may be placed underneath the wafer 504. This position of the displacement sensor 506 b may provide specific technical advantages. Specifically, when a robotic arm is used to move the wafer 504 to/from the system, the displacement sensor 506 b positioned below the wafer 504 will typically not interfere with the movement of the wafer 504 by the robotic arm as it lifts the wafer 504. Another technical advantage provided by this arrangement involves the effect of light-emitting displacement sensors on semiconductor devices. Typically, devices on the wafer may be laid out and exposed on the top side of the wafer 504. By placing the displacement sensor 506 b underneath the wafer 504, the system can avoid shining lasers or other high-intensity light sources onto these semiconductor devices. This may be advantageous when these semiconductor devices are particularly sensitive to high-intensity light.

FIG. 5C illustrates a plurality of displacement sensors 506 c, 508 c, according to some embodiments. In this example, a plurality of displacement sensors 506 c, 508 c may be positioned on a radial line 510 extending out for me center of the wafer 504. This allows the system to measure displacement data at multiple points at each angle of rotation. Although the example of FIG. 5C illustrates two displacement sensors 506 c, 508 c, this number of displacement sensors is provided only by way of example and is not meant to be limiting. Other embodiments may include more than two displacement sensors. With multiple displacement sensors measuring displacement data along the radial line 510, the system can generate a displacement map of multiple locations on the wafer 504 to create a displacement mapping of the entire surface of the wafer 504 rather than just the edge of the wafer. Prior to this disclosure, a metrology station that performs a laser scan of the entire surface of the wafer 504 was required in order to generate an accurate view of many different aspects of the wafer 504. However, the metrology station is expensive and time-consuming to operate. Providing a plurality of displacement sensors 506 c, 508 as depicted in FIG. 5C may replace at least a portion of the operations performed by the metrology station with a low-cost, high-speed process to provide a surface mapping of displacement data for the wafer 504.

FIG. 5D illustrates a plurality of displacement sensors 506 d, 508 d positioned at different rotational angles, according to some embodiments. Instead of placing the displacement sensors 506 d, 508 d along a same radial line at different radial distances, some embodiments may position the displacement sensors 506 d, 508 d at a same radial distance separated by a known angle of rotation 512. These embodiments may provide duplicate displacement data for a location as a backup in case one of the displacement sensors 506 d, 508 d fails. These embodiments may also use the duplicate displacement data to characterize, calibrate, and/or detect malfunctions in the displacement sensors 506 d, 508 d. Note that more than two displacement sensors may also be used without limitation. Another technical advantage provided by aligning multiple displacement sensors 506 d, 508 d at a same radial distance is the collection of parallel data for the wafer 504. For example, by placing the multiple displacement sensors 506 d, 508 d approximately 180° apart on the wafer 504, the entire wafer perimeter may be measured in one half rotation rather than a full rotation. Similarly, by placing four displacement sensors approximately 90° apart on the wafer 504, the entire wafer perimeter may be measured in one quarter rotation rather than a full rotation. These configurations can thus reduce the total time required to collect the displacement data by 50%, 25%, etc.

Combinations of the different displacement sensor numbers and/or locations illustrated in FIGS. 5A-5B may be used in any combination and without limitation. For example, some embodiments may include multiple displacement sensors at different angles of rotation and/or different radial distances on a top side of the wafer, while optionally including additional displacement sensors at different angles of rotation and/or different radial distances on a bottom side of the wafer. Some embodiments may also use different sensor types or settings when multiple displacement sensors are used. For example some embodiments may use multiple laser displacement sensors, each operating with a different light frequency. Different frequencies may reflect differently off of the wafer, so using different light frequencies for different sensors may improve the accuracy of the overall displacement data measurement. Additionally, some embodiments may use different sensor types when multiple displacement sensors are used. For example, a laser displacement sensor may be used in one location while an ultrasonic displacement sensor may be used in another location.

FIG. 6 illustrates a three-dimensional (3D) graph 600 of the displacement data, according to some embodiments. The graph 600 includes distance measurements relative to a default or baseline displacement of the wafer. Locations on the wafer may be mapped into Cartesian coordinates on a millimeter scale. These coordinates may be assigned based on the alignment data for the notch. For example, the notch location may be assigned a coordinate position of (0, 150) in the (x, y) plane of the graph 600. Thus, once the alignment position in the displacement data have been captured, some embodiments may rotate the displacement data to conform with the coordinate locations based on the notch location.

In this example, the displacement data is stored as a vertical distance relative to a baseline location. For example, a ring 602 may represent a baseline location of the wafer when no bow or warping is present. The data points 604 representing distances measured above the baseline location may be represented as positive displacements. These data points 604 may correspond to locations on the wafer that have bowed or warped upwards relative to a center of the wafer. Data points 606 representing distances measured below the baseline location may be represented as negative displacements. These data points 606 may correspond to locations on the wafer that have bowed or warped downwards relative to a center of the wafer.

The displacement data may be stored for each wafer as it is rotated on the platform. Additionally, displacement data may be stored for each displacement sensor in the system measuring the wafer. Displacement data from various displacement sensors may be combined for a single wafer to generate a 3D mapping of displacements throughout the surface of the wafer. This displacement data may then be passed to other machines in the semiconductor processing pipeline and used to control operations on those machines as described below.

FIG. 7A illustrates a baseline wafer 704 that may be measured by a displacement sensor 706, according to some embodiments. The baseline wafer 704 may be an ideal flat wafer in the z-plane. In other words, the baseline wafer 704 may generate a displacement data that shows a constant baseline displacement 720 that aligns with the surface of the wafer 704. The displacement data received from the baseline wafer 704 may be used to characterize the relative displacement of other subsequent wafers that are measured by the system. The baseline wafer 704 may be measured as part of a calibration or initialization process for the system. The displacement data from subsequent measurements of subsequent wafers may be subtracted from the displacement data from the baseline wafer. Although not shown explicitly in FIG. 7A, embodiments that include multiple displacement sensors may store baseline displacement data for each sensor. Displacement data measured from subsequent wafers may be subtracted from the baseline displacement data for each corresponding displacement sensor.

FIG. 7B illustrates a convex wafer 704 b, according to some embodiments. A convex profile indicates that the wafer 704 b has bowed or warped downwards at the edges of the wafer 704 b relative to the center of the wafer. A displacement 722 may be larger than the baseline displacement 720, resulting in negative values for the displacement 722 when subtracted from the baseline displacement 720. Similarly, FIG. 7C illustrates a concave wafer 704 c, according to some embodiments. A concave profile indicates that the wafer 704 c has bowed or warped upwards at the edge of the wafer 704 c relative to the center of the wafer. A displacement 724 may be smaller than the baseline displacement 720, resulting in positive values for the displacement 724 when subtracted from the baseline displacement 720.

FIG. 8 illustrates a graph 800 of displacement data for warped wafers, according to some embodiments. Instead of being mapped to 2D coordinates on a 3D axis, the displacement data may be mapped to a 2D axis, where the x-axis indicates an angle of rotation, and the y-axis indicates a displacement relative to a baseline. The mapping to the angle of rotation may also be based on the alignment data to determine an origin for the rotation. Displacement data 802 corresponds to a wafer that may include concave and/or convex portions. This type of wafer may be characterized as an “potato chip” shape that ripples up and down along the edge of the wafer. Displacement data 804 corresponds to a wafer with one side that curls or warps upwards. Graph 800 illustrates how displacement data for any type of warped or bow condition in wafer may be characterized by the system described herein.

The mapping to the 2D coordinates of FIG. 6 , or the mapping to angles rotation in FIG. 8 may be used to control subsequent processes. For example, the 2D coordinates of FIG. 6 may be used to identify 2D regions in the wafer that should be polished more heavily, cleaned more heavily, or be subject to differential pressures during a polishing process. For example, these differential pressures may include lower pressures in some areas and higher pressure in other areas to compensate for irregularities in the wafer as represented in the displacement data. Contiguous areas of displacement on a wafer may be grouped together into a region and mapped to a particular pressurized chamber in the CMP carrier head. These regions on the wafer may be identified in the mapped data described above.

FIG. 9 illustrates a flowchart 900 of different processes the may be executed as part of a semiconductor manufacturing process, according to some embodiments. Note that a wafer may have been processed using various semiconductor machines prior to the beginning of the flowchart 900, such as machines that perform various deposition processes, etch processes, and so forth. After these processes have been executed, a robotic arm may move the wafer onto the wafer aligner/displacement measurement system 902. This system 902 may be implemented using the system 400 described above. The wafer aligner/displacement measurement system 902 may generate displacement data 908.

The robotic arm may move the wafer onto a CMP machine 904 to perform a CMP process. The displacement data 908 may be transmitted to a handling control 910 and/or the endpoint control 912 for the CMP machine 904. The displacement data may then be used to control the polishing process performed on the wafer. Specifically, the CMP machine 904 may include a carrier head that grips or holds the wafer. The carrier head may be associated with a number of parameters. These parameters may control an angle at which the wafer is gripped by the carrier head, and/or amount of pressure applied to the wafer at various locations. These parameters may be adjusted on the carrier had to compensate for areas on the wafer that are bowed or warped during the cleaning or polishing processes described below.

For example, the displacement data 908 may be used to control how the handling control 910 grips the wafer. For example, a flat wafer may be gripped with more force by the carrier head than a bowed wafer. The CMP machine may receive the displacement data and adjust the grip force applied to the wafer based on an amount of displacement identified in the displacement data. Additionally, if the wafer bows along a portion of the wafer circumference, the handling control 910 may grip the wafer at a slight angle such that the bowed portion protrudes slightly more than the rest of the wafer away from the carrier head 140 on the CMP machine 100 illustrated in FIG. 1 . Additionally, the chambers 146 may be pressurized based on the displacement data 908. Specific chambers 146 that are behind warped portions of the wafer may be pressurized more than other chambers such that they push the warped portions in line with the rest of the wafer or apply greater pressure during the polishing process. This may generate a flat surface on the wafer as it is pushed against the polishing pad in the CMP machine 904. Because the orientation of the wafer is known from the alignment procedure, the displacement data may be mapped to specific chambers 146 in the carrier head 140 that are above the warped portions of the wafer. These chambers may be pressurized more or less based on the positive/negative displacement data associated with each corresponding region of the wafer.

The displacement data 908 may also be used by the endpoint control 912 of the CMP process performed by the CMP machine 904. For example, a real-time thickness of a top layer film on the wafer may be measured as the wafer is polished using the process described above in FIGS. 1-3 . For example, a flat wafer may be polished faster and with more force than a bowed or warped wafer. Without access to the displacement data, the polishing process generally uses an average or worst-case polishing speed/pressure to accommodate both flat and warped wafers. However, when the wafer can be characterized as flat or warped using the displacement data, the speed/pressure applied during the polishing process can be adjusted accordingly. The CMP machine may use the displacement data to determine whether the wafer is flat, and if the wafer is flat the CMP machine may then increase the speed/pressure of the polishing process. If the wafer is not flat, then the CMP machine may decrease the speed or pressure of the polishing process. This may lead to a 5%-10% increase in throughput of wafers through the polishing process. The displacement data may also be provided to the CMP machine 904 to allow both flat and warped wafers to be polished to have similar desired post-polishing characteristics. For example, a bowed portion of the wafer may be polished more than the flat portion of the wafer to generate an overall flat surface on the wafer. Some embodiments may also adjust other parameters of the polishing process based on the displacement data. For example, a substantially flat wafer may use a higher temperature or a more abrasive slurry to polish faster, while a warped wafer may use a less abrasive slurry to polish more delicately or vice versa. Additionally, temperatures and chemical additives may be applied to different zones on the wafer at it is being polished. For example, a warped portion of the wafer may use a first chemical additive to the slurry and/or temperature, while a flat portion of the wafer may use a second chemical additive and/or temperature.

The measurement of the reflected wavelengths may be influenced by a displacement of the wafer from the polishing pad. The displacement data 908 may be used to compensate for locations on the wafer that may be bowed or warped and thus may lead to inaccurate thickness measurements of the surface being polished. For example, positive displacement data indicating that the wafer bows towards the polishing pad may add or subtract a proportional amount from a thickness measurement based on the effect of the displacement on the reflected wavelengths received by the spectrometer. Ultimately, in endpoint may be adjusted to polish warped portions of the wafer more than other portions of the wafer to produce an overall flat surface on the wafer for a subsequent step in the semiconductor manufacturing pipeline.

Next, the wafer may be moved to a cleaner 906 or wafer cleaning machine that is configured to clean the wafer from debris left after the polishing process. The displacement data 908 may be passed to the handling control 914 of the cleaner 906 and/or to the software implementing a cleaning recipe 916. The cleaner 906 may include a carrier head similar to the carrier had described above for the CMP machine 904 Next, the displacement data 908 may also be used to control a cleaning process performed on the wafer. For example, the handling control 914 may be altered to grip the wafer differently based on the displacement data such that it is more uniformly oriented for the cleaning process as described above for the polishing process. Additionally, the cleaning recipe 916 may be altered based on the warp/bow profile of the wafer. Portions of the wafer corresponding to a warped region may be cleaned more or less based on relative positive/negative values in the displacement data. For example, a pressure with which a brush is applied to the wafer may be adjusted with the positive/negative displacement data to apply more or less pressure to protruding areas of the wafer in the cleaning machine.

FIG. 10 illustrates a flowchart 1000 of a method for measuring displacement of wafers during semiconductor manufacturing processes, according to some embodiments. The method may include rotating a wafer around a center of the wafer (1002). This rotation may be performed as the wafer is supported on a platform as illustrated above in FIG. 4 . This rotation may also simultaneously be used to locate and alignment notch on the wafer using an alignment sensor.

The method may further include measuring a displacement of the wafer at a predetermined distance from the center of the wafer as the wafer is rotated to generate displacement data (1004). The predetermined distance may correspond to a position at which the displacement sensor reads displacement data from the wafer. The predetermined distance may be located along an outer edge of the wafer, at any point along a radial line extending from a center of the wafer, and/or at an angle displacement from the alignment sensor or from another displacement sensor as illustrated above in FIGS. 5A-5D. The displacement data may characterize displacement measurements from a plurality of different displacement sensors. The displacement sensor may be implemented using a laser displacement sensor or any other type of displacement sensor configured to measure distances.

The method may additionally include using the displacement data to control a polishing or cleaning process performed on the wafer (1006). This portion of the method may be optional, and some executions of the method may use displacement data to characterize the wafer without using the displacement data to control any other processes. For example, the displacement data may be used to characterize a wafer surface and/or to characterize or test a previous process performed on the wafer. Controlling the polishing process may include using the displacement data to adjust a handling control and/or alter an orientation at which a carrier head secures the wafer. Controlling the polishing process may also include using the displacement data to apply varying amounts of pressure on a backside of the wafer to compensate for bows in the wafer as it is pushed against a polishing pad. Some embodiments may also use the displacement data to control other processes, such as a cleaning process.

The optional step of using the displacement data to control a polishing or cleaning process performed on the wafer may be executed by a computer system of the corresponding polishing machine or cleaning machine. For example, software instructions on the computer system of a polishing machine may cause one or more processors to receive the displacement data generated using the displacement sensor. As described above, the displacement data may indicate at least one area on the wafer that is bowed or warped. These instructions may also cause the machine to identify a parameter of the carrier head corresponding to a location on the area of the wafer that is bowed or warped. The computer system may then adjust that parameter on the carrier head to compensate for the area on the wafer that is bowed or warped. As described above, these parameters may adjust an angle at which a carrier head grips the wafer, may adjust a pressure applied during the polishing process, may adjust an orientation of the wafer during a process, may adjust pressures applied to the back of the wafer using various chambers in the carrier head, and/or the like.

It should be appreciated that the specific steps illustrated in FIG. 10 provide particular methods of measuring displacement of wafers between semiconductor manufacturing processes according to various embodiments. Other sequences of steps may also be performed according to alternative embodiments. For example, alternative embodiments may perform the steps outlined above in a different order. Moreover, the individual steps illustrated in FIG. 10 may include multiple sub-steps that may be performed in various sequences as appropriate to the individual step. Furthermore, additional steps may be added or removed depending on the particular applications. Many variations, modifications, and alternatives also fall within the scope of this disclosure.

Machine-Learning Control Using Displacement Data

As described above, the process of generating metrology data for a wafer may be a computationally complex and time-consuming process, often requiring a special metrology chamber that may incur a significant cost on a wafer manufacturer. For example, a metrology station may perform a laser scan of a surface of the wafer to identify displacements, such as bows or warps in the wafer shape, along with other irregularities in the surface or shape of the wafer. Metrology data may also be used to measure thicknesses of thin films and other features on the wafer. For example, metrology data may include thicknesses or locations of metal traces, semiconductor circuits, or other features that have been formed on the wafer. A metrology station that performs the laser scan or other analysis of the wafer may require a significant amount of time to perform this analysis, which may take from a few minutes to up to an hour, depending on the size of the wafer and the resolution of the scan.

Some of the embodiments described herein may use the displacement data generated using the systems and methods described above to replace and/or generate the metrology data without requiring the use of a metrology station for each new wafer. This practical application of machine-learning principles using specific displacement data inputs to generate control signals or metrology data significantly improves the wafer manufacturing process by eliminating the need for a complex metrology station and the need to perform a complex metrology scan on every new wafer. Instead, the displacement sensor system described above may be used to generate displacement data, and a trained model may then be used to generate the necessary control signals for a polishing or cleaning process. Some embodiments may also generate or select metrology data that may be representative of the wafer without performing a full metrology scan. This increases the throughput of the wafer manufacturing process, and may eliminate the metrology station from the wafer manufacturing pipeline. This in turn reduces the wear-and-tear on the metrology station and increases its serviceable lifetime.

FIG. 11 illustrates a block diagram 1100 of a process for training a model, according to some embodiments. As described above, one or more displacement sensors may be located relative to a rotating platform to receive a wafer 1104. As the platform rotates, the one or more displacement sensors may measure displacement data 1112 for the wafer 1104. The one or more displacement sensors may be part of a displacement measurement system 1106, which may include any of the embodiments described above. For example, the displacement measurement system 1106 may include an alignment sensor that locates a notch in the wafer 1104. Generally, the displacement sensor measures a displacement of the wafer 1104 relative to the one or more displacement sensors. For example, the one or more displacement sensors may measure a distance between the one or more displacement sensors and a surface of the wafer 1104 as the wafer 1104 is rotated.

In addition to generating the displacement data 1112, other sensors 1108 may be present in some embodiments to generate additional sensor data. The sensors 1108 may be part of the displacement measurement system 1106. The sensors 1108 may alternatively or additionally be included in other systems or processing chambers used to process the wafer 1104 earlier in the wafer manufacturing pipeline. The sensors 1108 may generate sensor data 1114 that may also be used as an input when training or using the model 1122. The sensors 1108 may include a camera that captures an image of the wafer 1104 as the sensor data 1114. The sensors 1108 may also include eddy current sensors that may be used to determine thicknesses of copper films on the wafer 1104. The sensors 1108 may also include rotational accelerometers or other sensors configured to measure a position or geometry of the wafer 1104. Note that some embodiments may use the displacement data 1112 alone, while other embodiments may augment the displacement data 1112 with the additional sensor data 1114. Other embodiments may rely on the sensor data 1114 without requiring the displacement data 1112.

The model 1122 may be trained based on the type of outputs that the model 1122 needs to generate. In the example of FIG. 11 , the model 1122 may be trained to generate metrology data. In order to train the model 1122, a metrology station 1102 may perform a metrology analysis on the wafer 1104. The metrology station 1102 may generate metrology data 1110. In some embodiments, a full set of metrology data from the metrology station 1102 may be used as the metrology data 1110 for training the model 1122. In other embodiments, a subset of the data points in the metrology data generated by the metrology station 1102 may be included in the metrology data 1110 for training the model 1122. For example, the metrology data 1110 may include film thicknesses or displacement measurements at a subset of predetermined locations on the wafer 1104. Displacement data for the wafer 1104 may be captured at multiple points in radii across a surface of the wafer 1104. Note that the displacement data 1112 from the displacement measurement system 1106 may include displacement data captured at a predetermined radius of the wafer 1104 as it is rotated. The metrology data 1110 may include a full 2D set of measurements across the surface of the wafer 1104, which may include the predetermined radius of the displacement measurement system 1106, along with displacement measurements at a plurality of additional radii to map the full surface of the wafer 1104.

To train the model 1122, the displacement data 1112, along with the sensor data 1114 (which may be included optionally) may be provided as training data 1118 for training the model 1122. The model 1122 may be implemented using any type of classification model. For example, the training data 1118 may be used by a minimization regression algorithm to set the weights or node values in the model 1122. For example, the model 1122 may be implemented using a logistic regression model, a k-nearest neighbor model, a decision tree, a support vector machine, a Naïve Bayes model, a random forest, a gradient boosting model, and/or any other classification model type. Labels 1120 for the training data 1118 may be generated using the metrology data 1110. For example, the model 1122 may be configured to output a classification of a shape of the wafer 1104. The metrology data 1110 may be used to select one of the shape outputs of the model 1122 to be used as a label 1120 on the training data 1118. Alternatively, the model 1122 may be configured to output a displacement mapping that includes displacement measurements for locations on the wafer 1104, and the metrology data 1110 may use the displacement values in the 2D mapping of the wafer 1104 as the label 1120 for the training data 1118.

Note that the example of FIG. 11 trains the model 1122 using metrology data to generate characteristics or metrology data for the wafer. This allows metrology data to be generated by the model 1122 based on the displacement data 1112 without requiring metrology station 1102 for subsequent wafers that are processed by the system when using the trained model 1122. However, other models 1122 may be trained to generate control signals for a cleaning or polishing process rather than metrology data. Although not shown explicitly in FIG. 11 , the metrology data 1110 used as the labels 1120 for training the model 1122 may be replaced using control signals that match the geometry of the wafer 1104.

For example, the metrology data 1110 may be used to select or calculate control signal values for the cleaning or polishing process. If a bow on one side of the wafer 1104 is detected by the displacement data 1112 or the metrology data 1110, a control signal for a polishing process may increase a polishing pressure on a zone of the polishing head that is behind the area of the wafer 1104 with the bow. These control signals may be selected as labels 1120 based on the metrology data 1110 or the displacement data 1112, depending on the embodiment.

FIG. 12 illustrates a block diagram 1200 of a system for using a trained model to control a cleaning or polishing process, according to some embodiments. After training the model 1122 using the process described above in FIG. 11 , the process may bypass the metrology station and instead use the displacement data 1112. The displacement data 1112 may be provided as an input to the trained model 1122. Optionally, some embodiments may also include other sensor data from additional sensors if that sensor data was used to train the model 1122. The model 1122 may propagate these inputs through its internal layers and nodes of the model 1122 to generate a classification output that classifies the displacement data 1112. This classification may generate outputs that may be used to control a polishing or cleaning process.

In this example, controlling the cleaning or polishing process may include selecting from among a plurality of different cleaning or polishing processes. For example, a first cleaning or polishing process 1202-1 may be executed on a wafer that is substantially flat. Thus, the polishing or cleaning process may be executed in a higher rate. In contrast, a second cleaning or polishing process 1202-2 may be configured to polish wafers with significant bows or warpage, and thus may polish the wafers more carefully at a slower rate. Therefore, the classification performed by the model 1122 may be integrated into the overall wafer manufacturing pipeline to individually classify wafers and maintain parallel lanes of manufacture that are optimized to the wafer type. By funneling wafers that are substantially flat into the first polishing or cleaning process 1202-1, these wafers may be polish significantly faster, and the bottleneck wafers may be funneled to the second polishing or cleaning process 1202-2, which may be executed in parallel and separately. This improves the overall throughput of the process and allows the speed of each individual polishing or cleaning process to be optimized to specific wafer geometries, rather than needing to accommodate any wafer geometry. For example, instead of selecting a polishing rate that will accommodate all wafer surface geometries, each of the plurality of polishing or cleaning processes 1202 may be optimized to handle a specific type (e.g., flat, bowed, warped, “potato chip” shaped, etc.).

FIG. 13 illustrates a block diagram 1300 of a process for using a model to generate control signals for a cleaner polishing process, according to some embodiments. In this example, the model 1122 may have been trained to generate specific control signals that may be used to control a cleaning or polishing process for the wafer. When receiving displacement data 1112 as an input, the model 1122 may generate control signals 1302 that may be provided as part of a recipe or a real-time control signal for a cleaning or polishing process 1202-1. For example, the outputs of the model 1122 may be included as part of a recipe, where the recipe includes control signals for all of the processes that are part of a semiconductor manufacturing step. The recipe may then be provided to the cleaning or polishing process to be executed. Alternatively, the control signals 1122 may be provided to the process directly as it runs. This allows the model 1122 to provide real-time control for the cleaning or polishing process.

Although not shown explicitly in FIG. 13 , some embodiments may include an intermediate step from FIG. 12 to generate metrology data. For example, the model 1122 may generate metrology data as described above. The metrology data may then be used to select or set the control signals illustrated in FIG. 13 . For example, a film thickness determined by the metrology data may be used to control a polishing speed or pressure for that portion of the wafer.

The control signals generated by the model 1122 may include any of the inputs that may be provided to any semiconductor manufacturing process. In this specific case of a polishing or cleaning process, control signals may be provided to control a rotation speed 1302-1 of a platen or pedestal that supports the wafer in the cleaning or polishing process. The control signals may also include a head rotation speed 1302-2 for a head that rotates and holds the wafer against a polishing or cleaning pad. As described above, the speeds of rotation for each of these two parameters may be adjusted based on the displacement data and surface geometry of the wafer. The control signals may also control a flow of slurry used in a polishing or cleaning process. This may include a flow rate for the slurry, as well as a type of slurry used. For example, a more abrasive slurry may be used when a more aggressive polish is needed in order to improve the overall processing time. As described above, some polishing or cleaning heads may include zones that allow different pressures to be applied to different portions of the wafer in the polishing or cleaning head. The control signals may include zone pressures 1302-4 for each of these different zones. For example, increasing the pressure on a particular zone that corresponds to a bowed portion of the wafer may provide a more aggressive polish or cleaning to that wafer area.

Note that the control signals provided to the cleaning or polishing process 1202-1 that are illustrated in FIG. 13 are provided only by way of example and are not meant to be limiting. A cleaning or polishing process may include many additional controls, such as a temperature control, a flow rate for various gases or other substances in the chamber, a chamber pressure control, and/or other environmental parameter controls. Some embodiments may also provide each of these controls as a time series of values, such that the control values change over time. For example, the model 1122 may be trained to generate a time series output of speeds for the head rotation speed 1302-2. A high-speed may be used at first in order to level the bowed portions of the wafer, and the speed may gradually slow to perform a more uniform and careful polish on the flattened wafer as a whole.

FIG. 14 illustrates a block diagram 1400 of how the model may be used to produce metrology data 1402, according to some embodiments. Note that the model 1122 need not be required to provide values for the full data set in the metrology data 1402. Instead, some embodiments may provide a subset of the values in the metrology data 1402. For example, the displacement data 1112 and/or other sensor data 1116 may be used to characterize a thickness of a film on the surface of the wafer. This thickness may be used to populate fields in the metrology data 1402. Thus, the metrology data 1402 may include less than the full set of metrology data 1402.

In some embodiments, a subset of values provided by the model 1122 may be combined with other values from actual metrology process to generate the full metrology data set 1402. For example, the metrology process may be reduced such that only a subset of the values are measured and the overall metrology process time is reduced. The remaining values may be populated using the model 1122. In other embodiments, the model 1122 may estimate all of the metrology data 1402. For example, many of the values in the metrology data 1402 may be strongly correlated with the shape and topology of the wafer as measured by the displacement data 1112. The model 1122 may be trained to recognize these correlations and generate estimated values for the metrology data 1402 based on the measured displacements.

In some embodiments, the model 1122 may be trained to select sets of pre-existing metrology data that may be used to populate the metrology data 1402. For example, the metrology data 1402 may include data fields that characterize a thickness of a film on the wafer. Multiple sets of values for these thickness data fields may be stored from previous wafer tests or training data. When the model 1122 receives the sensor data 1116, the model 1122 may be configured to select one of the pre-existing data sets characterizing the thickness of the film on the wafer. The same process may be used to select pre-existing data sets for any other set of fields in the metrology data 1402.

FIG. 15 illustrates a flowchart 1500 of a method for training and using a model with displacement data, according to some embodiments. The method may include receiving displacement data generated using a displacement sensor (1502). The displacement data may be measured for a wafer, and the displacement data may indicate a displacement of the wafer relative to the displacement sensor. In some embodiments, this may include rotating a wafer around a center of the wafer and measuring a displacement of the wafer at a predetermined distance from the center of the wafer. Some embodiments may also measure additional sensor data as described above.

The method may additionally include providing the displacement data to a model that is trained using metrology data sets and corresponding displacement data sets (1504). For example, the displacement data may be provided to the model as labeled training data sets from previous wafer processes. The model may be trained as a classification model to recognize known patterns in the displacement data and other inputs and to subsequently select a corresponding set of outputs based on the categorization of the inputs.

The method may further include generating metrology data for the wafer based on output from the model in response providing the displacement data as input to the model (1506). Some embodiments may generate control signals for a cleaning or polishing chamber based on output from the model. The output of the model may be used to control the cleaning or polishing process for that same wafer in a subsequent processing chamber. For example, multiple cleaning or polishing pipelines with varying speeds may be arranged where the output of the model routes wafers into different polishing processes based on the flatness of the wafers. The output from the model may include control signals that control polishing pressure, speed, slurry flow, polishing materials, and so forth, based on the wafer displacement data.

Each of the methods described herein may be implemented by a computer system. Each step of these methods may be executed automatically by the computer system, and/or may be provided with inputs/outputs involving a user. For example, a user may provide inputs for each step in a method, and each of these inputs may be in response to a specific output requesting such an input, wherein the output is generated by the computer system. Each input may be received in response to a corresponding requesting output. Furthermore, inputs may be received from a user, from another computer system as a data stream, retrieved from a memory location, retrieved over a network, requested from a web service, and/or the like. Likewise, outputs may be provided to a user, to another computer system as a data stream, saved in a memory location, sent over a network, provided to a web service, and/or the like. In short, each step of the methods described herein may be performed by a computer system, and may involve any number of inputs, outputs, and/or requests to and from the computer system which may or may not involve a user. Those steps not involving a user may be said to be performed automatically by the computer system without human intervention. Therefore, it will be understood in light of this disclosure, that each step of each method described herein may be altered to include an input and output to and from a user, or may be done automatically by a computer system without human intervention where any determinations are made by a processor. Furthermore, some embodiments of each of the methods described herein may be implemented as a set of instructions stored on a tangible, non-transitory storage medium to form a tangible software product.

FIG. 16 illustrates an exemplary computer system 1600, in which various embodiments may be implemented. The computer system 1600 may be used to implement any of the computer systems described above. For example, the computer system 1600 may be used to control the displacement sensor and store the displacement data. The computer system 1600 may also be used to transmit the displacement data to other semiconductor manufacturing machines, such as a CMP machine or a cleaner. The CMP machine and/or the cleaner may also include a computer system 1600 that controls the polishing and/or cleaning process using the displacement data.

As shown in the figure, computer system 1600 includes a processing unit 1604 that communicates with a number of peripheral subsystems via a bus subsystem 1602. These peripheral subsystems may include a processing acceleration unit 1606, an I/O subsystem 1608, a storage subsystem 1618 and a communications subsystem 1624. Storage subsystem 1618 includes tangible computer-readable storage media 1622 and a system memory 1610.

Bus subsystem 1602 provides a mechanism for letting the various components and subsystems of computer system 1600 communicate with each other as intended. Although bus subsystem 1602 is shown schematically as a single bus, alternative embodiments of the bus subsystem may utilize multiple buses. Bus subsystem 1602 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. For example, such architectures may include an Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus, which can be implemented as a Mezzanine bus manufactured to the IEEE P1386.1 standard.

Processing unit 1604, which can be implemented as one or more integrated circuits (e.g., a conventional microprocessor or microcontroller), controls the operation of computer system 1600. One or more processors may be included in processing unit 1604. These processors may include single core or multicore processors. In certain embodiments, processing unit 1604 may be implemented as one or more independent processing units 1632 and/or 1634 with single or multicore processors included in each processing unit. In other embodiments, processing unit 1604 may also be implemented as a quad-core processing unit formed by integrating two dual-core processors into a single chip.

In various embodiments, processing unit 1604 can execute a variety of programs in response to program code and can maintain multiple concurrently executing programs or processes. At any given time, some or all of the program code to be executed can be resident in processor(s) 1604 and/or in storage subsystem 1618. Through suitable programming, processor(s) 1604 can provide various functionalities described above. Computer system 1600 may additionally include a processing acceleration unit 1606, which can include a digital signal processor (DSP), a special-purpose processor, and/or the like.

I/O subsystem 1608 may include user interface input devices and user interface output devices. User interface input devices may include a keyboard, pointing devices such as a mouse or trackball, a touchpad or touch screen incorporated into a display, a scroll wheel, a click wheel, a dial, a button, a switch, a keypad, audio input devices with voice command recognition systems, microphones, and other types of input devices. User interface input devices may include, for example, motion sensing and/or gesture recognition devices such as the Microsoft Kinect® motion sensor that enables users to control and interact with an input device, such as the Microsoft Xbox® 360 game controller, through a natural user interface using gestures and spoken commands. User interface input devices may also include eye gesture recognition devices such as the Google Glass® blink detector that detects eye activity (e.g., ‘blinking’ while taking pictures and/or making a menu selection) from users and transforms the eye gestures as input into an input device (e.g., Google Glass®). Additionally, user interface input devices may include voice recognition sensing devices that enable users to interact with voice recognition systems (e.g., Siri® navigator), through voice commands.

User interface input devices may also include, without limitation, three dimensional (3D) mice, joysticks or pointing sticks, gamepads and graphic tablets, and audio/visual devices such as speakers, digital cameras, digital camcorders, portable media players, webcams, image scanners, fingerprint scanners, barcode reader 3D scanners, 3D printers, laser rangefinders, and eye gaze tracking devices. Additionally, user interface input devices may include, for example, medical imaging input devices such as computed tomography, magnetic resonance imaging, position emission tomography, medical ultrasonography devices. User interface input devices may also include, for example, audio input devices such as MIDI keyboards, digital musical instruments and the like.

User interface output devices may include a display subsystem, indicator lights, or non-visual displays such as audio output devices, etc. The display subsystem may be a cathode ray tube (CRT), a flat-panel device, such as that using a liquid crystal display (LCD) or plasma display, a projection device, a touch screen, and the like. In general, use of the term “output device” is intended to include all possible types of devices and mechanisms for outputting information from computer system 1600 to a user or other computer. For example, user interface output devices may include, without limitation, a variety of display devices that visually convey text, graphics and audio/video information such as monitors, printers, speakers, headphones, automotive navigation systems, plotters, voice output devices, and modems.

Computer system 1600 may comprise a storage subsystem 1618 that comprises software elements, shown as being currently located within a system memory 1610. System memory 1610 may store program instructions that are loadable and executable on processing unit 1604, as well as data generated during the execution of these programs.

Depending on the configuration and type of computer system 1600, system memory 1610 may be volatile (such as random access memory (RAM)) and/or non-volatile (such as read-only memory (ROM), flash memory, etc.) The RAM typically contains data and/or program modules that are immediately accessible to and/or presently being operated and executed by processing unit 1604. In some implementations, system memory 1610 may include multiple different types of memory, such as static random access memory (SRAM) or dynamic random access memory (DRAM). In some implementations, a basic input/output system (BIOS), containing the basic routines that help to transfer information between elements within computer system 1600, such as during start-up, may typically be stored in the ROM. By way of example, and not limitation, system memory 1610 also illustrates application programs 1612, which may include client applications, Web browsers, mid-tier applications, relational database management systems (RDBMS), etc., program data 1614, and an operating system 1616. By way of example, operating system 1616 may include various versions of Microsoft Windows®, Apple Macintosh®, and/or Linux operating systems, a variety of commercially-available UNIX® or UNIX-like operating systems (including without limitation the variety of GNU/Linux operating systems, the Google Chrome® OS, and the like) and/or mobile operating systems such as iOS, Windows® Phone, Android® OS, BlackBerry® 10 OS, and Palm® OS operating systems.

Storage subsystem 1618 may also provide a tangible computer-readable storage medium for storing the basic programming and data constructs that provide the functionality of some embodiments. Software (programs, code modules, instructions) that when executed by a processor provide the functionality described above may be stored in storage subsystem 1618. These software modules or instructions may be executed by processing unit 1604. Storage subsystem 1618 may also provide a repository for storing data used in accordance with some embodiments.

Storage subsystem 1600 may also include a computer-readable storage media reader 1620 that can further be connected to computer-readable storage media 1622. Together and, optionally, in combination with system memory 1610, computer-readable storage media 1622 may comprehensively represent remote, local, fixed, and/or removable storage devices plus storage media for temporarily and/or more permanently containing, storing, transmitting, and retrieving computer-readable information.

Computer-readable storage media 1622 containing code, or portions of code, can also include any appropriate media, including storage media and communication media, such as but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage and/or transmission of information. This can include tangible computer-readable storage media such as RAM, ROM, electronically erasable programmable ROM (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disk (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other tangible computer readable media. This can also include nontangible computer-readable media, such as data signals, data transmissions, or any other medium which can be used to transmit the desired information and which can be accessed by computing system 1600.

By way of example, computer-readable storage media 1622 may include a hard disk drive that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive that reads from or writes to a removable, nonvolatile magnetic disk, and an optical disk drive that reads from or writes to a removable, nonvolatile optical disk such as a CD ROM, DVD, and Blu-Ray® disk, or other optical media. Computer-readable storage media 1622 may include, but is not limited to, Zip® drives, flash memory cards, universal serial bus (USB) flash drives, secure digital (SD) cards, DVD disks, digital video tape, and the like. Computer-readable storage media 1622 may also include, solid-state drives (SSD) based on non-volatile memory such as flash-memory based SSDs, enterprise flash drives, solid state ROM, and the like, SSDs based on volatile memory such as solid state RAM, dynamic RAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, and hybrid SSDs that use a combination of DRAM and flash memory based SSDs. The disk drives and their associated computer-readable media may provide non-volatile storage of computer-readable instructions, data structures, program modules, and other data for computer system 1600.

Communications subsystem 1624 provides an interface to other computer systems and networks. Communications subsystem 1624 serves as an interface for receiving data from and transmitting data to other systems from computer system 1600. For example, communications subsystem 1624 may enable computer system 1600 to connect to one or more devices via the Internet. In some embodiments communications subsystem 1624 can include radio frequency (RF) transceiver components for accessing wireless voice and/or data networks (e.g., using cellular telephone technology, advanced data network technology, such as 3G, 4G or EDGE (enhanced data rates for global evolution), WiFi (IEEE 802.11 family standards, or other mobile communication technologies, or any combination thereof), global positioning system (GPS) receiver components, and/or other components. In some embodiments communications subsystem 1624 can provide wired network connectivity (e.g., Ethernet) in addition to or instead of a wireless interface.

In some embodiments, communications subsystem 1624 may also receive input communication in the form of structured and/or unstructured data feeds 1626, event streams 1628, event updates 1630, and the like on behalf of one or more users who may use computer system 1600.

By way of example, communications subsystem 1624 may be configured to receive data feeds 1626 in real-time from users of social networks and/or other communication services such as Twitter® feeds, Facebook® updates, web feeds such as Rich Site Summary (RSS) feeds, and/or real-time updates from one or more third party information sources.

Additionally, communications subsystem 1624 may also be configured to receive data in the form of continuous data streams, which may include event streams 1628 of real-time events and/or event updates 1630, that may be continuous or unbounded in nature with no explicit end. Examples of applications that generate continuous data may include, for example, sensor data applications, financial tickers, network performance measuring tools (e.g. network monitoring and traffic management applications), clickstream analysis tools, automobile traffic monitoring, and the like.

Communications subsystem 1624 may also be configured to output the structured and/or unstructured data feeds 1626, event streams 1628, event updates 1630, and the like to one or more databases that may be in communication with one or more streaming data source computers coupled to computer system 1600.

Computer system 1600 can be one of various types, including a handheld portable device (e.g., an iPhone® cellular phone, an iPad® computing tablet, a PDA), a wearable device (e.g., a Google Glass® head mounted display), a PC, a workstation, a mainframe, a kiosk, a server rack, or any other data processing system.

Due to the ever-changing nature of computers and networks, the description of computer system 1600 depicted in the figure is intended only as a specific example. Many other configurations having more or fewer components than the system depicted in the figure are possible. For example, customized hardware might also be used and/or particular elements might be implemented in hardware, firmware, software (including applets), or a combination. Further, connection to other computing devices, such as network input/output devices, may be employed. Based on the disclosure and teachings provided herein, other ways and/or methods to implement the various embodiments should be apparent.

In the foregoing description, for the purposes of explanation, numerous specific details were set forth in order to provide a thorough understanding of various embodiments. It will be apparent, however, that some embodiments may be practiced without some of these specific details. In other instances, well-known structures and devices are shown in block diagram form.

The foregoing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the foregoing description of various embodiments will provide an enabling disclosure for implementing at least one embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of some embodiments as set forth in the appended claims.

Specific details are given in the foregoing description to provide a thorough understanding of the embodiments. However, it will be understood that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may have been shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may have been shown without unnecessary detail in order to avoid obscuring the embodiments.

Also, it is noted that individual embodiments may have been described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may have described the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed, but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.

The term “computer-readable medium” includes, but is not limited to portable or fixed storage devices, optical storage devices, wireless channels and various other mediums capable of storing, containing, or carrying instruction(s) and/or data. A code segment or machine-executable instructions may represent a procedure, a function, a subprogram, a program, a routine, a subroutine, a module, a software package, a class, or any combination of instructions, data structures, or program statements. A code segment may be coupled to another code segment or a hardware circuit by passing and/or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc., may be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, etc.

Furthermore, embodiments may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks may be stored in a machine readable medium. A processor(s) may perform the necessary tasks.

In the foregoing specification, features are described with reference to specific embodiments thereof, but it should be recognized that not all embodiments are limited thereto. Various features and aspects of some embodiments may be used individually or jointly. Further, embodiments can be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the specification. The specification and drawings are, accordingly, to be regarded as illustrative rather than restrictive.

Additionally, for the purposes of illustration, methods were described in a particular order. It should be appreciated that in alternate embodiments, the methods may be performed in a different order than that described. It should also be appreciated that the methods described above may be performed by hardware components or may be embodied in sequences of machine-executable instructions, which may be used to cause a machine, such as a general-purpose or special-purpose processor or logic circuits programmed with the instructions to perform the methods. These machine-executable instructions may be stored on one or more machine readable mediums, such as CD-ROMs or other type of optical disks, floppy diskettes, ROMs, RAMs, EPROMs, EEPROMs, magnetic or optical cards, flash memory, or other types of machine-readable mediums suitable for storing electronic instructions. Alternatively, the methods may be performed by a combination of hardware and software. 

What is claimed is:
 1. A system comprising: one or more displacement sensors positioned to measure a displacement of a wafer as the wafer is rotated on a platform; a cleaning or polishing chamber configured to clean or polishing the wafer; and a computer system configured to perform operations comprising: receiving, for the wafer, displacement data generated using the one or more displacement sensors, wherein the displacement data indicates displacement of the wafer relative to the one or more displacement sensors; providing the displacement data to a model that is trained using displacement data sets; generating control signals for the cleaning or polishing chamber based on output from the model in response to receiving the displacement data as input; and using the control signals to control the cleaning or polishing process for the wafer.
 2. The system of claim 1, wherein controlling the cleaning or polishing process for the wafer comprises selecting the cleaning or polishing process from a plurality of different cleaning or polishing processes, wherein the cleaning or polishing process has a shorter run time than at least one of the plurality of different cleaning or polishing processes.
 3. The system of claim 1, wherein controlling the cleaning or polishing process for the wafer comprises controlling a rotation speed of a platen that supports the wafer in the cleaning or polishing process.
 4. The system of claim 1, wherein controlling the cleaning or polishing process for the wafer comprises controlling a rotation speed of a cleaning or polishing head in the cleaning or polishing process.
 5. The system of claim 1, wherein controlling the cleaning or polishing process for the wafer comprises controlling a flow of slurry used in the cleaning or polishing process.
 6. The system of claim 1, wherein controlling the cleaning or polishing process for the wafer comprises controlling a pressure applied to a zone in a cleaning or polishing head in the cleaning or polishing process.
 7. The system of claim 1, wherein the displacement data indicates an area on the wafer that is bowed or warped.
 8. A method comprising: receiving, for a wafer, displacement data generated using a displacement sensor, wherein the displacement data indicates displacement of the wafer relative to the displacement sensor; providing the displacement data to a model that is trained using metrology data sets and corresponding displacement data sets; and generating metrology data for the wafer based on output from the model in response to receiving the displacement data as input to the model.
 9. The method of claim 8, further comprising: using the metrology data to control a cleaning or polishing process for the wafer.
 10. The method of claim 8, wherein the metrology data comprises thicknesses of thin films or features on the wafer.
 11. The method of claim 8, further comprising: rotating a wafer around a center of the wafer; and measuring a displacement of the wafer at a predetermined distance from the center of the wafer as the wafer is rotated to generate the displacement data.
 12. The method of claim 11, further comprising: measuring a displacement of a baseline wafer to generate baseline displacement data representing a flat wafer surface.
 13. The method of claim 12, wherein generating the displacement data comprises determining a displacement of the wafer relative to the baseline displacement data.
 14. The method of claim 11, further comprising mapping the displacement data to two-dimensional coordinates on the wafer based on alignment data.
 15. The method of claim 11, further comprising mapping the displacement data to angles of rotation on the wafer based on alignment data.
 16. The method of claim 11, further comprising identifying a displacement area on the wafer in the displacement data, and providing the displacement area to the polishing or cleaning process.
 17. A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving, for a wafer, displacement data generated using a one or more displacement sensors, wherein the displacement data indicates displacement of the wafer relative to the one or more displacement sensors; providing the displacement data to a model that is trained using displacement data sets; and generating control signals for a cleaning or polishing chamber based on output from the model in response to receiving the displacement data as input.
 18. The non-transitory computer-readable medium of claim 17, wherein the operations further comprise: using the control signals to control the cleaning or polishing process for the wafer.
 19. The non-transitory computer-readable medium of claim 18, wherein controlling the cleaning or polishing process for the wafer comprises controlling a rotation speed of a platen that supports the wafer in the cleaning or polishing process.
 20. The non-transitory computer-readable medium of claim 18, wherein controlling the cleaning or polishing process for the wafer comprises selecting the cleaning or polishing process from a plurality of different cleaning or polishing processes. 